Predicting Success for Web Product through Key Performance Indicators based on Balanced Scorecard with the Use of Machine Learning

Abstract

Machine Learning (ML) can be proved as an important tool in planning better business strategies. For the purposes of the present study, the prospect for the development of an electronic platform by a technology firm providing financial services is explored. The purpose of this article is to demonstrate the ways in which a start-up can predict the success of an online platform prior to its market launch. The prediction is achieved by applying Artificial Intelligence (AI) on Key Performance Indicators (KPIs) derived from the customers’ perspective, as shown in the Balanced Scorecard (BSC). The research methodology was quantitative and online questionnaires were used to collect empirical quantitative data related to bank loans. Subsequently, KPIs were created based on the collected data, to measure and assess the success of the platform. The effectiveness of the model was calculated up to 91.89%, and thus, it is estimated that the online platform will be of great success with 91.89% validity. In conclusion, prediction was found to be crucial for businesses to prevent a dire economic situation. Finally, the necessity for businesses to keep up with technological advances is highlighted.

Automating Financial Regulatory Compliance With Ai: A Review and Application Scenarios

“…Their research methodology involved collecting empirical data and creating KPIs to measure and assess the success of an online platform. This study illustrates the effectiveness of AI in predicting the success of financial products and services, thereby aiding in strategic decision-making (Tagkouta et al, 2023). Finally, Cernisevs, Popova, and Cernisevs, (2023) explore the risk-based approach for selecting company key performance indicators (KPIs) in the context of financial services.…”

“…By aligning KPIs with the unique risk profile of a company, this approach introduces an innovative method for performance measurement within the financial industry, particularly in the context of Fintech companies (Cernisevs, Popova, & Cernisevs, 2023). Tagkouta et al (2023) explore the use of machine learning in predicting the success of web products through KPIs based on the Balanced Scorecard (BSC). Their research methodology involved collecting empirical data and creating KPIs to measure and assess the success of an online platform.…”